Exploring causality mechanism in the joint analysis of longitudinal and survival data

Lei Liu, Cheng Zheng, Joseph Kang

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

In many biomedical studies, disease progress is monitored by a biomarker over time, eg, repeated measures of CD4 in AIDS and hemoglobin in end-stage renal disease patients. The endpoint of interest, eg, death or diagnosis of a specific disease, is correlated with the longitudinal biomarker. In this paper, we examine and compare different models of longitudinal and survival data to investigate causal mechanisms, specifically, those related to the role of random effects. We illustrate the methods by data from two clinical trials: an AIDS study and a liver cirrhosis study.

Original languageEnglish
Pages (from-to)3733-3744
Number of pages12
JournalStatistics in medicine
Volume37
Issue number26
DOIs
StatePublished - Nov 20 2018

Keywords

  • interaction
  • mediation analysis
  • moderator
  • repeated measures
  • shared random effects

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